7 papers
SFR-Net: Learning Scale-Frustum Representations for Ultra-Wide Area Remote Sensing Image Segmentation
Chuyu Zhong, Keyan Chen, Qinzhe Yang +3
Pixel count and geographical coverage are two key characteristics of remote sensing images. Existing remote sensing image segmentation methods typically focus on images with either…
Radiative-Structured Neural Operator for Continuous Spectral Super-Resolution
Ziye Zhang, Bin Pan, Zhenwei Shi
Spectral super-resolution (SSR) aims to reconstruct hyperspectral images (HSIs) from multispectral observations, with broad applications in computer vision and remote sensing. Deep…
A Copula-Guided Temporal Dependency Method for Multitemporal Hyperspectral Images Unmixing
Ruiying Li, Bin Pan, Qiaoying Qu +2
Multitemporal hyperspectral unmixing (MTHU) aims to model variable endmembers and dynamical abundances, which emphasizes the critical temporal information. However, existing method…
SMILE: A Super-resolution Guided Multi-task Learning Method for Hyperspectral Unmixing
Ruiying Li, Bin Pan, Qiaoying Qu +2
The performance of hyperspectral unmixing may be constrained by low spatial resolution, which can be enhanced using super-resolution in a multitask learning way. However, integrati…
Preserving Domain Generalization in Fine-Tuning via Joint Parameter Selection
Bin Pan, Shiyu Shen, Zongbin Wang +2
Domain generalization seeks to develop models trained on a limited set of source domains that are capable of generalizing effectively to unseen target domains. While the predominan…
Hyperspectral Image Generation with Unmixing Guided Diffusion Model
Shiyu Shen, Bin Pan, Ziye Zhang +1
We address hyperspectral image (HSI) synthesis, a problem that has garnered growing interest yet remains constrained by the conditional generative paradigms that limit sample diver…